Eye Examination Test Anomalous Light Detection
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Solution Overview
Problem
Conventional online eye examination tests are affected by uncontrolled and potentially non-ideal environmental lighting conditions, which can impact the accuracy of the results.
Innovation Solution
A method using a computing device with an image capturing unit to analyze the user's surroundings by dividing the image into bins, estimating light intensity, identifying areas with anomalous light, and adjusting the examination accordingly, ensuring that the environment does not significantly impact the test results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the eye examination test is performed in an uncontrolled home environment, then the accessibility and convenience of the test are improved, but the accuracy and reliability of the test results deteriorate due to uncontrolled lighting conditions
Solution Approach 1:
The system performs preliminary analysis of the environment by capturing an image of the user and surroundings before conducting the eye examination test. The processor divides the captured image into bins, estimates light intensity in each bin, and identifies areas with anomalous light intensity in advance, allowing the system to prepare appropriate adjustments before the actual test begins
Solution Approach 2:
The system continuously monitors lighting conditions during the eye examination test by analyzing captured images and providing feedback about anomalous light areas. This feedback mechanism allows the system to adjust the examination process in real-time based on the detected environmental conditions, ensuring accurate results even in uncontrolled home environments
2Measurement precision
If the computing device analyzes and adjusts for anomalous light conditions, then the measurement precision of the eye examination is improved, but the device complexity increases due to additional image processing requirements
Solution Approach 1:
The processor divides the captured image into multiple bins (horizontal and vertical segments) to analyze light intensity distribution across different regions of the image. This segmentation approach simplifies the complex task of environmental analysis by breaking it down into manageable discrete regions that can be processed independently
Solution Approach 2:
The system introduces an intermediary image capturing unit and processing layer between the user and the eye examination test. This intermediary component captures the environment, analyzes lighting conditions, and provides adjusted examination parameters or corrections, thereby isolating the core examination function from environmental variations without requiring direct modification of the user's environment
Data Source
AI summary
A method of performing an eye examination test for examining eyes of a user, said method using a computing device, said computing device comprising an image capturing unit arranged for capturing images, said method comprising the steps of capturing, by said capturing unit, an image of said user and its surroundings, dividing, by said computing device, said captured image into a plurality of bins, estimating, by said computing device, light intensity of each of said plurality bins, determining, by said computing device, an area of anomalous light intensity in said captured image based on said step of estimation wherein said estimated light intensity is above a predetermined threshold value, performing, by said computing device, said eye examination test, taking said determined area of anomalous light into account.